Abstract
The water balance model, which was used to simulate the water balance and water distribution, consists of several modules, each describing one part of the hydrological system: Bare soil evaporation, transpiration by vegetation, processes related to ice and snow (snow accumulation and snow melt), surface runoff, groundwater recharge, and finally river runoff at the catchment outlet. These are described in the next sections, then the model sensitivity and uncertainty is assessed to identify the most important parameters for which the according input dataset are described. Before applying the water balance model, its accuracy is evaluated with different measures and against other datasets and model results.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Notes
- 1.
If the computing time was limited, a factorial set up could have been introduced, where only a given number of ‘levels’ are chosen for each parameter or possible interaction among factors are examined (cf. [50, 52]). However, this was not necessary as the uncertainty was only run for one point and not the raster data set.
- 2.
Moderate-Resolution Imaging Spectroradiometer.
- 3.
Tropical Rainfall Measuring Mission.
- 4.
http://lpdaac.usgs.gov/get_data, accessed 15.07.2009.
- 5.
http://earthexplorer.usgs.gov/, accessed 15.07.2009.
- 6.
http://glcf.umiacs.umd.edu/data/srtm/index.shtml, accessed 31.01.2008.
- 7.
The data is available for over 9,000 stations, including many airport and additional city locations worldwide, and provides daily summaries for mean, min, max, and dewpoint temperature, wind speed, pressure, visibility, precipitation and snowdepth (http://hurricane.ncdc.noaa.gov/cdo/info.html#GSOD, accessed 08.09.2011).
- 8.
http://glovis.usgs.gov/, accessed 4.10.2009.
- 9.
http://www.worldclim.org/, accessed 24.05.2010.
- 10.
http://mirador.gsfc.nasa.gov/collections/TRMM_3B43__006.shtml, accessed 08.09.2011.
- 11.
References
Bremicker, M., Luce, A., Haag, I., & Sieber, A. (2005). Das Wasserhaushaltsmodell Larsim: Modellgrundlagen (80 p) Retrieved 15 May, 2011, from http://www.hvz.baden-wuerttemberg.de/pdf/LARSIM_DE_2005-06-24.pdf.
Uhlenbrook, S. (1999). Untersuchung und Modellierung der Abflussbildung in einem mesoskaligen Einzugsgebiet (201 p). Institut für Hydrologie der Universität Freiburg i. Br., Freiburg (Freiburger Schriften zur Hydrologie, 10).
Beven, K. J. (2001). How far can we go in distributed hydrological modelling? Hydrology and Earth System Sciences, 5(1), 1–12.
Aerts, J. C., Kriek, M., & Schepel, M. (1999). Spatial tools for river basins and environment and analysis of management options (STREAM): Set up and requirements. Physics and Chemistry of the Earth Part B Hydrology Oceans and Atmosphere, 24(6), 591–595.
Bäse, F. (2005). Beurteilung der Parametersensitivität und der Vorhersagesicherheit am Beispiel des hydrologischen Modells J2000 (102 p). Unpublished diploma thesis, Friedrich-Schiller Universität Jena.
Bouwer, L. M., Aerts, J. C., Droogers, P., & Dolman, A. J. (2006). Detecting the long-term impacts from climate variability and increasing water consumption on runoff in the Krishna river basin (India). Hydrology and Earth System Sciences, 10, 703–713.
Glugla, G. & Fürtig, G. (1997). Dokumentation zur Anwendung des Rechenprogramms ABIMO (37 p). Bundesanstalt für Gewässerkunde, Berlin.
Meßer, J. (1997). Auswirkungen der Urbanisierung auf die Grundwasserneubildung im Ruhrgebiet unter besonderer Berücksichtigung der Castroper Hochfläche und des Stadtgebietes Herne, Essen (58 p). Deutsche Montan Technologie GmbH (DMT-Berichte aus Forschung und Entwicklung).
Meßer, J. (2008). Ein vereinfachtes Verfahren zur Berechnung der flächendifferenzierten Grundwasserneubildung in Mitteleuropa (60 p). Lippe: Lippe Wassertechnik.
Haase, D. (2009). Effects of urbanisation on the water balance: A long-term trajectory. Environmental Impact Assessment Review, 29, 211–219.
Schmidt, G., Gretzschel, O., Volk, M., & Uhl, M. (2003). Konzept zur skalenspezifischen Modellierung des Wasser- und Stoffhaushaltes im Projekt FLUMAGIS: A concept for the scale-specific simulation of water-bound material fluxes in the project FLUMAGIS. In K. Hennrich, M. Rode, A. Bronstert (Eds.), 6. Workshop zur großskaligen Modellierung in der Hydrologie—Flussgebietsmanagement (pp. 7–20). Kassel: University Press.
Glugla, G., Jankiewicz, P., Rachimow, C., Lojek, K., Richter, K., Fürtig, G., & Krahe, P. (2003). Wasserhaushaltsverfahren zur Berechnung vieljähriger Mittelwerte der tatsächlichen Verdunstung und des Gesamtabflusses (102 p). BfG, Koblenz (BfG-Bericht, 1342).
Kite, G. (2000). Using a basin-scale hydrological model to estimate crop transpiration and soil evaporation. Journal of Hydrology, 229, 59–69.
Simonneaux, V., Duchemin, B., Helson, D., Er-Raki, S., Olioso, A., & Chehbouni, A. (2008). The use of high-resolution image time series for crop classification and evapotranspiration estimate over an irrigated area in Central Morocco. International Journal of Remote Sensing, 29(1), 95–116.
Zhao, C., Nan, Z., & Cheng, G. (2005). Methods for estimating irrigation needs of spring wheat in the middle Heihe Basin, China. Agricultural Water Management, 75, 54–70.
Armbruster, V. (2002). Grundwasserneubildung in Baden-Württemberg (140 p). Dissertation. Institut für Hydrologie der Universität Freiburg i. Br., (Freiburger Schriften zur Hydrologie, 17).
Merz, R., Blöschl, G., & Parajka, J. (2006). Spatio-temporal variability of event runoff coefficients. Journal of Hydrology, 331(3–4), 591–604.
Huintjes, E., Li, H., Sauter, T., Li, Z., & Schneider, C. (2010). Degree-day modelling of the surface mass balance of Urumqi Glacier No. 1, Tian Shan, China. The Cryosphere Discussions, 4, 207–232.
Neitsch, S. L., Arnold, J. G., Kiniry, J. R., & Williams, J. R. (2005). Soil and water assessment tool theoretical documentation: Version 2005 (476 p). Temple: Grassland, Soil and Water Research Laboratory.
Buttafuoco, G., Caloiero, T., & Coscarelli, R. (2010). Spatial uncertainty assessment in modelling reference evapotranspiration at regional scale. Hydrology and Earth System Sciences, 14(11), 2319–2327.
Aguilar, C., & Polo, M. J. (2011). Calculation of reference evapotranspiration surfaces in distributed hydrological modelling at different temporal scales. Hydrology and Earth System Sciences Discussions, 8, 4813–4850.
Contreras, S., Jobbágy, E. G., Villagra, P. E., Nosetto, M. D., & Puigdefábregas, J. (2011). Remote sensing estimates of supplementary water consumption by arid ecosystems of central Argentina. Journal of Hydrology, 397(1–2), 10–22.
Allen, R. G. (1998). Crop evapotranspiration: Guidelines for computing crop water requirements (300 p). Rome (FAO irrigation and drainage paper, 56): Food and Agriculture Organisation of the United Nations.
DVWK (1996). Ermittlung der Verdunstung von Land- und Wasserflächen: DVWK-Merkblätter zur Wasserwirtschaft (135 p). Wirtschafts- und Verl.-Ges. Gas und Wasser, Bonn (Gas und Wasser, 238).
Iqbal, M. (1983). An introduction to solar radiation (390 p). Toronto: Academic Press.
Schulla, J. (1997). Hydrologische Modellierung von Flussgebieten zur Abschätzung der Folgen von Klimaänderungen (163 p). Dissertation, Dresden (Zürcher Geographische Schriften, 69).
Allen, R. G. (1986). A Penman for all seasons. Journal of Irrigation and Drainage Engineering, 112(4), 348–368.
Monteith, J. L. (1965). Evaporation and environment. In G. E. Fogg (Ed.), Symposium of the society for experimental biology: The state and movement of water in living organisms (Vol. 19, pp. 205–234). New York: Academic Press.
Penman, H. L. (1948). Natural evaporation from open water, bare soil and grass. Proceedings of the Royal Society of London. Series A Mathematical and Physical Science, 193(1032), 120–145.
Hurtalová, T., Matejka, F., Roznovsky, J., & Janous, D. (2003). Aerodynamic resistance of spruce forest stand in relation to roughness length and airflow. Contributions to Geophysics and Geodesy, 33(3), 147–160.
Lindroth, A. (1993). Aerodynamic and canopy resistance of short-rotation forest in relation to leaf area index and climate. Boundary-Layer Meteorology, 66, 265–279.
Tiyip, T., Taff, G. N., Kung, H.-T., & Zhang, F. (2010). Remote sensing assessment of salinisation impacts in the Tarim Basin: The Delta Oasis of the Ugan and Kuqa Rivers. In G. Schneier-Madanes & M.-F. Courel (Eds.), Water and sustainability in arid regions. Bridging the gap between physical and social sciences (pp. 15–32). Dordrecht: Springer Science+Business Media B.V.
Thom, A. S., & Oliver, H. R. (1977). On Penman’s equation for estimating regional evapotranspiration. Quarterly Journal of the Royal Meteorological Society, 103, 345–357.
Vietinghoff, H. (2000). Die Verdunstung freier Wasserflächen: Grundlagen, Einflußfaktoren und Methoden der Ermittlung (113 p). UFO, Atelier für Gestaltung und Verlag, Allensbach (Ufo Naturwissenschaft, 201).
Wimmer, F., Schlaffer, S., Aus der Beek, T., & Menzel, L. (2009). Distributed modelling of climate change impacts on snow sublimation in Northern Mongolia. Advances in Geosciences, 21, 117–124.
Knauf, D. (1976). Die Abflußbildung in schneebedeckten Einzugsgebieten des Mittelgebirges (155 p). Institut für Hydraulik und Hydrologie Darmstadt, Darmstadt (Technische Berichte, 17).
Rango, A., & Martinec, J. (1995). Revisiting the degree-day method for snowmelt computations. Water Resources Bulletin, 31(4), 657–669.
Bagchi, A. K. (1983). Areal value of degree-day factor. Hydrological Sciences Journal/Journal Sciences Hydrologiques, 28(4), 499–511.
Kuusisto, E. (1980). On the values and variability of degree-day melting factor in Finland. Nordic Hydrology, 11, 235–242.
Martinec, J., Rango, A., & Roberts, R. (2008). Snowmelt runoff model (SRM) user’s manual: Edited by Enrique Gómez-Landesa & Max P. Bleiweiss (178 p). Las Cruces: New Mexico State University.
Shin, H. J., Park, M. J., Ha, R., Yi, J. E., Kim, G. S., & Kim, S.-J. (2011). Evaluation of snow melt contribution to streamflow in a heavy snowfall watershed of South Korea using SWAT model. Toledo, Spain: SWAT 2011.
Neitsch, S. L., Arnold, J. G., Kiniry, J. R., Srinivasan, R., & Williams, J. R. (2009). Soil and water assessment tool: Input/output file documentation Version 2009 (604 p). Temple: Grassland, Soil and Water Research Laboratory.
Merz, R., & Blöschl, G. (2004). Regionalisation of catchment model parameters. Journal of Hydrology, 287, 95–123.
Kondo, J., & Yamazaki, T. (1990). A prediction model for snowmelt, snow surface temperature and freezing depth using a heat balance method. Journal of Applied Meteorology, 29, 375–384.
Hock, R. (2003). Temperature index melt modelling in mountain areas. Journal of Hydrology, 282, 102–115.
Beven, K. J. (1991). Spatially distributed modelling: Conceptual approach to runoff prediction. In D. S. Bowles (Ed.), Recent advances in the modelling of hydrologic systems. Proceedings of the NATO Advanced Study Institute on Recent Advances in the Modelling of Hydrologic Systems, Sintra, Portugal 10–23 July, 1988 (pp. 373–387). Dordrecht: Kluwer.
International Soil Reference and Information Centre (ISRIC) (2011). Soil and terrain database for China. Version 1.0—scale 1:1 million. ISRIC Wageningen. Retrieved from 5 Oct, 2011. http://www.isric.org/data/soil-and-terrain-database-china.
Batjes, N. (2002). Soil parameter estimates for the soil types of the world for use in global and regional modelling (Version 2.1., 46 p). Wageningen: ISRIC Report, 2002/02c, International Food Policy Research Institute and International Soil Reference and Information Centre. Retrieved 25 Mar, 2011, from http://www.isric.eu/isric/webdocs/docs/ISRIC_Report_2002_02c.pdf.
Meinrath, G., & Schneider, P. (2007). Quality assurance for chemistry and environmental science: Metrology from pH measurement to nuclear waste disposal (326 p). Berlin, Heidelberg: Springer.
Hamby, D. M. (1994). A review of techniques for parameter sensitivity analysis of environmental models. Environmental Monitoring Assessment, 32, 135–154.
Campolongo, F., Kleijnen, J., & Andres, T. (2004). Screening Methods. In A. Saltelli (Ed.), Sensitivity analysis (pp. 65–80). Chichester: Wiley.
Campolongo, F., Saltelli, A., Sorensen, T., & Tarantola, S. (2004). Hitchhiker’s guide to sensitivity analysis. In A. Saltelli (Ed.), Sensitivity Analysis (pp. 15–47). Chichester: Wiley.
Lenhart, T., Eckhardt, K., Fohrer, N., & Frede, H. G. (2002). Comparison of two different approaches of sensitivity analysis. Physics and Chemistry of the Earth, Parts A/B/C, 27(9–10), 645–654.
Harlin, J., & Kung, C.-S. (1992). Parameter uncertainty and simulation of design floods in Sweden. Journal of Hydrology, 137, 209–230.
Frühwirth, R., & Regler, M. (1983). Monte-Carlo-Methoden: Eine Einführung (171 p). Mannheim: Bibliogr. Inst.
Lin, S., Jing, C., Chaplot, V., Yu, X., Zhang, Z., Moore, N., et al. (2010). Effect of DEM resolution on SWAT outputs of runoff sediment and nutrients. Hydrology and Earth System Sciences Discussions, 7, 4411–4435.
Liu, T., Willems, P., Pan, X. L., Bao, A. M., Chen, X., Veroustraete, F., et al. (2011). Climate change impact on water resource extremes in a headwater region of the Tarim basin in China. Hydrology and Earth System Sciences, 15, 3511–3527.
U.S. Geological Survey (2005). Shuttle Radar Topography Mission, version 2, 3-arc second resolution. Global Land Cover Facility, University of Maryland, College Park, Maryland Retrieved 31 Jan, 2008, from http://glcf.umiacs.umd.edu/data/srtm/index.shtml.
U.S. Geological Survey & Japan ASTER Programme (2009). ASTER GDEM Version 1. NASA Land Processes Distributed Active Archive Center, Sioux Falls, Retrieved 15 Jul, 2009, from http://earthexplorer.usgs.gov/.
Aster Validation Team (2009). ASTER global dem validation summary report: ASTER GDEM validation team: METI/ERSDAC, NASA/LPDAAC, USGS/EROS in cooperation with NGA and other collaborators (28 p). Retrieved 19 Oct, 2011, from https://lpdaac.usgs.gov/lpdaac/content/download/4009/20069/version/3/file/ASTER+GDEM+Validation+Summary+Report.pdf.
Albertz, J. (2001). Einführung in die Fernerkundung: Grundlagen der Interpretation von Luft- und Satellitenbildern (249 p). Darmstadt: Wiss. Buchges.
Sabins, F. F. (2007). Remote sensing: Principles and interpretation (494 p). Ill: Waveland Press, Long Grove.
Hengl, T., & Reuter, H. (2011). How accurate and usable is GDEM? A statistical assessment of GDEM using LiDAR data. Geomorphometry, 45–48.
Hirt, C., Filmer, M. S., & Featherstone, W. E. (2010). Comparison and validation of the recent freely available ASTER-GDEM ver1, SRTM ver4.1 and GEODATA DEM-9S ver3 digital elevation models over Australia: Australian Journal of Earth Sciences. Australian Journal of Earth Sciences, 57(3), 337–347.
Zhang, W., & Montgomery, D. R. (1994). Digital elevation model grid size, landscape representation, and hydrologic simulations. Water Resources Research, 30(4), 1019–1028.
Jacobsen, K. (2010). Comparison of ASTER GDEMs with SRTM Height Models. In R. Reuter (Ed.), 30th EARSeL symposium remote sensing for science, education, and natural and cultural heritage (pp. 521–526). Paris, France: UNESCO.
Wang, G. Q., Zhang, J. Y., Jin, J. L., Pagano, T. C., Calow, R., Bao, Z. X., et al. (2012). Assessing water resources in China using PRECIS projections and a VIC model. Hydrology and Earth System Sciences, 16, 231–232.
Di Luzio, M., Arnold, J. G., & Srinivasan, R. (2005). Effect of GIS data quality on small watershed stream flow and sediment simulations. Hydrological Processes, 19(3), 629–650.
Kienzle, S. (2004). The Effect of DEM Raster Resolution on First Order, Second Order and Compound Terrain Derivatives. Transactions in GIS, 8(1), 83–111.
de Vente, J., Poesen, J., Govers, G., & Boix-Fayos, C. (2009). The implications of data selection for regional erosion and sediment yield modelling. Earth Surface Processes and Landforms, 34(15), 1994–2007.
Bosch, D. D., Sheridan, J. M., Batten, H. L., & Arnold, J. G. (2004). Evaluation of the SWAT model on a coastal plain agricultural watershed. Transactions of the American Society of Agricultural Engineers, 47(5), 1493–1506.
Dixon, B., & Earls, J. (2009). Resample or not?! Effects of resolution of DEMs in watershed modelling. Hydrological Processes, 23(12), 1714–1724.
Tulu, M. D. (February, 2005). SRTM DEM suitability in runoff studies (87 p). Retrieved 19 Oct, 2011, from http://www.itc.nl/library/papers_2005/msc/wrem/mesay.pdf.
Terribile, F., Coppola, A., Langella, G., Martina, M., & Basile, A. (2011). Potential and limitations of using soil mapping information to understand landscape hydrology. Hydrology and Earth System Sciences Discussions, 8, 4927–4977.
Bruneau, P., Gascuel-Odoux, C., Robin, P., Merot, P., & Beven, K. J. (1995). Sensitivity to space and time resolution of a hydrological model using digital elevation data. Hydrological Processes, 9, 69–81.
ESRI (2010): ArcGIS, Version 10.0 [Computer program], Redlands, CA.
Autonomous Region Bureau of Surveying and Mapping (2004). Xinjiang-Weiyu’er-Zizhiqu-dituji: Xinjiang Uygur Autonomous Region Atlas (307 p). Beijing: Zhongguo ditu chubanshe.
Bubenzer, O., & Bolten, A. (2008). The use of new elevation data (SRTM/ASTER) for the detection and morphometric quantification of Pleistocene megadunes (draa) in the eastern Sahara and the southern Namib. Geomorphology, 102, 221–231.
National Oceanic and Atmospheric Administration of the U.S. Department of Commerce National Climatic Data Centre (NOAA NCDC) (2011). Global Summary of the Day Diwopu Station, Station Number 514635, 29.02.1985–31.12.2010. Retrieved 16 May, 2011, from http://www7.ncdc.noaa.gov/CDO/cdo.
National Oceanic and Atmospheric Administration of the U.S. Department of Commerce National Climatic Data Centre (NOAA NCDC) (2011). Global Summary of the Day Fukang Station, Station Number 513650, 28.03.1962–13.05.1997. Retrieved 23 Feb, 2010, from http://www7.ncdc.noaa.gov/CDO/cdo.
National Oceanic and Atmospheric Administration of the U.S. Department of Commerce National Climatic Data Centre (NOAA NCDC) (2011). Global Summary of the Day Shihezi Station, Station Number 513560, 21.08.1956–19.08.1996. Retrieved 23 Feb, 2010, from http://www7.ncdc.noaa.gov/CDO/cdo.
National Oceanic and Atmospheric Administration of the U.S. Department of Commerce National Climatic Data Centre (NOAA NCDC) (2011). Global Summary of the Day Wulumuqi Station, Station Number 514630, 22.08.1956–31.12.2010. Retrieved 16 May, 2011, from http://www7.ncdc.noaa.gov/CDO/cdo.
Peterson, T. C., Easterling, D. R., Karls, T. R., Groisman, P., Nicholls, N., Plummer, N., et al. (1998). Homogeneity adjustments of in situ atmospheric climate data: A review. International Journal of Climatology, 18, 1493–1517.
Dahmen, E. R., & Hall, M. J. (1990). Screening of hydrological data: Tests for stationarity and relative consistency (58 p). ILRI: Wageningen.
Barth, N. C. (2011). Auswertung der Temperatur- und Niederschlagsdaten von 15 Klimastationen im Umkreis von Urumqi (AR Xinjiang, China) (65 p). Heidelberg: Unpublished bachelor thesis, Ruprecht-Karls-Universität.
Daly, C. (2006). Guidelines for assessing the suitability of spatial climate data sets. International Journal of Climatology, 26, 707–721.
U.S. Geological Survey (2012a). Land surface temperature and emissivity daily L3 global 1 km Grid SIN. Retrieved 19 Mar, 2012, from https://lpdaac.usgs.gov/products/modis_products_table/mod11a1.
Ajami, N. K., Gupta, H., Wagener, T., & Sorooshian, S. (2004). Calibration of a semi-distributed hydrologic model for streamflow estimation along a river system. Journal of Hydrology, 298, 112–135.
Statistics Bureau of Urumqi (2000). Urumqi Statistical Yearbook 2000 (325 p). China Statistics Press: Beijing
Statistics Bureau of Urumqi (2005). Urumqi Statistical Yearbook 2005 (366 p). China Statistics Press: Beijing
Statistics Bureau of Urumqi (2006). Urumqi Statistical Yearbook 2006 (439 p). China Statistics Press: Beijing
Statistics Bureau of Urumqi (2008). Urumqi Statistical Yearbook 2008 (455 p). China Statistics Press: Beijing
Statistics Bureau of Urumqi (2009). Urumqi Statistical Yearbook 2009 (506 p). Beijing: China Statistics Press
Statistics Bureau of Urumqi (2010). Urumqi Statistical Yearbook 2010 (456 p). Beijing: China Statistics Press
Zhang, W., Ogawa, K., Ye, B., & Yamaguchi, Y. (2000). A monthly stream flow model for estimating the potential changes of river runoff on the projected global warming. Hydrological Processes, 14(10), 1851–1868.
NASA (2011). TRMM Rainfall Product TRMM_3B43, Monthly Average Rainfall, 0.25°×0.25° resolution. Retrieved 19 April, 2012, from http://mirador.gsfc.nasa.gov/collections/TRMM_3B43__006.shtml.
Hartkamp, A. D., Beurs, K., de Stein, A., & White, J. W. (1999). Interpolation techniques for climate variables (26 p). CIMMYT, Mexico, D.F. (NRG-GISÂ Series, 99-01).
Mitas, L., & Mitasova, H. (1999). Spatial interpolation. In P. A. Longley, M. F. Goodchild, D. J. Maguire & D. W. Rhind (Eds.), Geographical information systems. Principles, techniques, management and applications (pp. 481–492). Hoboken, NJ: Wiley.
Yan, J., Chen, X., Luo, G., & Guo, Q. (2006). Temporal and spatial variability response of groundwater level to land use/land cover change in oases of arid areas. Chinese Science Bulletin, 51(1), 51–59
Hunukumbura, P. B., Tachikawa, Y., & Shiiba, M. (2011). Distributed hydrological model transferability across basins with different hydro-climatic characteristics. Hydrological Processes. doi: 10.1002/hyp.8294.
ESRI. (2003). AcrGIS 9 Using ArcGIS Geostatistical Analyst (300 p). Redlands, CA: ESRI.
Javanmard, S., Yatagai, A., Nodzu, M. I., BodaghJamali, J., & Kawamoto, H. (2010). Comparing high-resolution gridded precipitation data with satellite rainfall estimates of TRMM_3B42 over Iran. Advances in Geosciences, 25, 119–125.
Aguilar, C., Herrero, J., & Polo, M. J. (2010). Topographic effects on solar radiation distribution in mountainous watersheds and their influence on reference evapotranspiration estimates at watershed scale. Hydrology and Earth System Sciences, 14(12), 2479–2494.
Statistics Bureau of Urumqi (2010). Urumqi Statistical Yearbook 2010 (456 p). Beijing: China Statistics Press.
Burns, I. S., Scott, S. N., Levick, L. R., Semmens, D. J., Miller, S. N., Hernandez, M., et al. (2007). Automated geospatial watershed assessment (AGWA) documentation (Version 2.0, 145 p). Tuscon, Arizona.
van Dijk, A. I., & Renzullo, L. J. (2011). Water resource monitoring systems and the role of satellite observations. Hydrology and Earth System Sciences, 15, 39–55.
NASA Landsat Program (2010). Landsat ETM+ scenes L1T, USGS, Sioux Falls. Retrieved from http://glovis.usgs.gov/
ERDAS (2010): ERDAS Imagine (Version 10) [Computer program], Norcross.
Chander, G., Markham, B.L., & Helder, D. L. (2009). Summary of current radiometric calibration coefficients for Landsat MSS, TM, ETM+, and EO-1 ALI sensors. Remote Sensing of the Environment, 113, 893–903.
Furby, S. L., & Campbell, N. A. (2001). Calibrating images from different dates to ‘like-value’ digital counts. Remote Sensing of Environment, 77, 186–196.
Beisl, U., Telaar, J., & Schönermark, M. v. (2008). Atmospheric correction, reflectance calibration and BRDF correction for ADS40 image data. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 37(B7), 7–12.
Callahan, K. E. (2003). Validation of a radiometric normalisation procedure for satellite derived imagery within a change detection framework (61 p). Master thesis: Utah State University.
El Hajj, M., Bégué, A., Lafrance, B., HAgolle, O., Dediau, G., & Rumeau, M. (2008). Relative radiometric normalisation and atmospheric correction of a SPOT 5 time series. Sensors, 8, 2774–2791.
Hong, G., & Zhang, Y. (2008). A comparative study on radiometric normalisation using high resolution satellite images. International Journal of Remote Sensing, 29(2), 425–438.
Schott, J. R., Salvaggio, C., & Volchok, W. J. (1988). Radiometric scene normalisation using Pseudoinvariant features. Remote Sensing of Environment, 26, 1–16.
Yuan, D., & Elvidge, C. D. (1996). Comparison of relative radiometric normalisation techniques. ISPRS Journal of Photogrammetry and Remote Sensing, 51, 117–126.
Brütt, A. (2005). Erstellung eines Moduls zur atmosphärischen Korrektur für optische Satellitendaten (67 p). Bachelorarbeit: Georg-August-Universität Göttingen.
Schöttker, B. (2002). Erfassung der Landbedeckung und Ableitung von Vegetationsveränderungen anhand multitemporaler LANDSAT-Daten in Westafrika (Benin) (152 p). Diploma thesis, Rheinische Friedrich-Wilhelms-Universität Bonn. Retrieved 19 Dec, 2008, from http://www.giub.uni-bonn.de/rsrg/www/docs/Schoettker_Diplomarbeit_2002.pdf.
Vogel, M. (2005). Erfassung von Vegetationsveränderungen in Namibia mit Hilfe von Fernerkundungs-Change-Detection-Verfahren und unter Berücksichtigung rezenter Niederschlagsereignisse (366 p). Dissertation, Julius-Maximilians-Universität Würzburg.
Neubert, M., & Meinel, G. (2005). Atmosphärische und topographische Korrektur von IKONOS-Daten mit ATCOR. In C. Heipke, K. Jacobsen & M. Gerke (Eds.), ISPRS Hannover Workshop 2005. High-Resolution Earth Imaging for Geospatial Information (17–20 May, 2005). Hannover International Archives of Photogrammetry and Remote Sensing, 36, 1–6.
Belward, A. S. (1991). Spectral characteristics of vegetation, soil and water in the visible, near-infrared and middle-infrared wavelength. In A. S. Belward & C. R. Valenzuela (Eds.), Remote sensing and geographical information systems for resource management in developing countries (pp. 31–53). Dordrecht: Kluwer.
Su, Z. (2000). Remote sensing of land use and vegetation for mesoscale hydrological studies. International Journal of Remote Sensing, 21(2), 213–233.
Kauth, R. J., & Thomas, G. S. (1976). The tasseled cap: a graphic description of the spectral-temporal development of agricultural crops as seen by LANDSAT. Symposium on Machine Processing of Remotely Sensed Data, 1976, 4B-41–4B-51 (June 29–July 1).
Franke, J. (2003). Analyse der Aussagefähigkeit verschiedener satellitengestützter Vegetationsindizes bezüglich der räumlichen Vegetationsverteilung (121 p). Unpublished dimploma thesis, Rheinische Friedirch-Wilhelms-Universität Bonn. Retrieved 19 Dec, 2008, from http://www.giub.uni-bonn.de/rsrg/www/docs/Franke_Diplomarbeit_2003.pdf.
Runnstrom, M. C. (2003). Rangeland development of the Mu Us Sandy Land in semi-arid China: An analysis using landsat and NOAA remote sensing data. Land Degradation and Development, 14(2), 189–202.
Sobrino, J. A., Jiménez-Muñoz, J. C., & Paolini, L. (2004). Land surface temperature retrieval from LANDSAT TM 5. Remote Sensing of Environment, 90(4), 434–440.
Huete, A. R. (1988). A soil-adjusted vegetation index (SAVI). Remote Sensing of Environment, 25, 295–309.
Karnieli, A., Gilad, U., Ponzet, M., Svoray, T., Mirzadinov, R., & Fedorina, O. (2008). Assessing land-cover change and degradation in the Central Asian deserts using satellite image processing and geostatistical methods. Journal of Arid Environments, 72, 2093–2105.
Congalton, R. G., & Green, K. (2009). Assessing the accuracy of remotely sensed data: Principles and practices (183 p). Boca Raton, FL: CRC Press.
Fricke, K. (2008). The development of Midong New District, Urumqi, PR China: Ecological and historical context and environmental consequences (165 p). Heidelberg University: Unpublished diploma thesis.
Congalton, R. G. (1991). A review of assessing the accuracy of classifications of remotely sensed data. Remote Sensing of Environment, 37, 35–46.
Jensen, J. R. (2005). Introductory digital image processing: A remote sensing perspective (526 p). Upper Saddle River, NJ: Prentice Hall.
Star, J. L. (Ed.) (2010). Integration of geographic information systems and remote sensing (225 p). Cambridge: Cambridge University Press.
Banerjee, M., Capozzoli, M., McSweeney, L., & Sinha, D. (1999). Beyond kappa. A review of interrater agreement measures. The Canadian Journal of Statistics, 27(1), 3–23.
Bastiaanssen, W. G., & Bandara, K. M. (2001). Evaporative depletion assessments for irrigated watersheds in Sri Lanka. Irrigation Science, 21, 1–15.
Foody, G. (2008). Harshness in image classification accuracy assessment. International Journal of Remote Sensing, 29(11), 3137–3158.
Shoshany, M. (2000). Satellite remote sensing of natural Mediterranean vegetation: A review within an ecological context. Progress in Physical Geography, 24(2), 153–178.
Abbaspour, K. C., Yang, J., Maximov, I., Siber, R., Bogner, K., Mieleitner, J., et al. (2007). Modelling hydrology and water quality in the pre-alpine/alpine Thur watershed using SWAT. Journal of Hydrology, 333(2–4), 413–430.
Water Affairs Bureau Urumqi (2003). Water Report 2003. Urumqi: Water Affairs Bureau Urumqi City, digital.
Water Affairs Bureau Urumqi (2004). Water Report 2004 (27 p). Urumqi: Water Affairs Bureau Urumqi City.
Water Affairs Bureau Urumqi (2005). Water Report 2005 (27 p). Urumqi: Water Affairs Bureau Urumqi City.
Water Affairs Bureau Urumqi (2007). Water Report 2007 (24 p). Urumqi: Water Affairs Bureau Urumqi City.
Liersch, S. (2005). Auswirkungen von Landnutzungsänderungen und umweltgerechten Bewirtschaftungsmethoden auf den Wasser- und Stoffhaushalt des Einzugsgebietes der Ems in Nordrhein-Westfalen: Modellierung einer Landnutzungssituation, die den Umweltstandards der EG-Wasserrahmenrichtlinie entspricht (120 p). Diploma thesis, Universität Potsdam.
Bieri, M., & Schleiss, A. J. (2010). Hydrologisch-hydraulische Modellierung von alpinen Einzugsgebieten mit komplexen Kraftwerksanlagen. In K. Weber, E. Fenrich, T. Gebler, M. Kramer & M. Noack (Eds.), 12. Treffen junger WissenschaftlerInnen an Wasserbauinstituten (pp. 99–105). Stuttgart: Institut für Wasserbau der Universität Stuttgart.
Martinec, J., & Rango, A. (1989). Merits of statistical criteria for the performance of hydrological models. Water Resources Bulletin, 25(2), 421–432.
Mu, Q., Zhao, M., & Running, S. W. (2011). MOD Global Terrestrial Evapotranspiration Dataset. Retrieved 27 Apr, 2012, from http://www.ntsg.umt.edu/project/mod16.
Mu, Q., Zhao, M., & Running, S. W. (2011). Improvements to a MODIS global terrestrial evapotranspiration algorithm. Remote Sensing of Environment, 115, 1781–1800.
Gassmann, P. W., Reyes, M. R., Green, C. H., & Arnold, J. G. (2007). The soil and water assessment tool: Historical development, applications, and future research directions. Transactions of the American Society of Agricultural and Biological Engineers, 50(4), 1211–1250.
Grassland, Soil and Water Research Laboratory (2011). ArcSWAT (Soil and Water Assessment Tool), Version 2009. Retrieved from http://www.swat.tamu.edu/software/arcswat.
Legesse, D., Abiye, T. A., Vallet-Coulomb, C., & Abate, H. (2010). Streamflow sensitivity to climate and land cover changes: Meki River, Ethiopia. Hydrology and Earth System Sciences, 14, 2277–2287.
Zhang, X., Chen, Y., Xia, J., & Yang, Q. (2011a). Impacts of climate change on the availability of water resources and water resources planning. In L. Ren, W. Wang & F. Yuan (Eds.), Proceedings of IWRM2010 Hydrological Cycle and Water Resources Sustainability in Changing Environments (Wallingford pp. 324–329, November 2010). Nanjing, China: IAHS Press.
Statistics Bureau of Xinjiang Uygur Autonomous Region (2005). Xinjiang Statistical Yearbook 2005. China Statistics Press, Beijing, CD-ROM.
Statistics Bureau of Xinjiang Uygur Autonomous Region (2006). Xinjiang Statistical Yearbook 2006. China Statistics Press, Beijing, CD-ROM.
Statistics Bureau of Xinjiang Uygur Autonomous Region (2007). Xinjiang Statistical Yearbook 2007. China Statistics Press, Beijing, CD-ROM.
Statistics Bureau of Xinjiang Uygur Autonomous Region (2009). Xinjiang Statistical Yearbook 2009. China Statistics Press, Beijing, CD-ROM.
Statistics Bureau of Xinjiang Uygur Autonomous Region (2010). Xinjiang Statistical Yearbook 2010. China Statistics Press, Beijing, CD-ROM.
Roth, K. (2011). Soil physics lecture notes: V2.0. Heidelberg: Institute of Environmental Physics, Heidelberg University.
Foken, T. (1990). Turbulenter Energieaustausch zwischen Atmosphäre und Unterlage: Methoden, meßtechnische Realisierung sowie ihre Grenzen und Anwendungsmöglichkeiten (287 p). Offenbach am Main: DWD.
Kelliher, F. M., Leuning, R., & Schulze, E. D. (1993). Evaporation and canopy characteristics of coniferous forests and grasslands. Oecologia, 95, 153–163.
Nakai, T., Sumida, A., Matsumoto, K., Daikuko, K., Iida, S., Park, H., et al. (2008). Aerodynamic scaling for estimating the mean height of dense canopy. Boundary-Layer Meteorology, 128, 423–443.
Rahman, K. (2011). Runoff simulation in a glacier dominated watershed using semi distributed hydrological model. International SWAT Conference 2011, Toledo, Spain. Retrieved 5 Oct, 2011, from http://swat.tamu.edu/media/40645/rahman.pdf.
Johnsson, H., & Lundin, L.-C. (1991). Surface runoff and soil water percolation as affected by snow and soil frost. Journal of Hydrology, 122(1–4), 141–159.
Rodriguez, E., Morris, C. S., Belz, J. E., Chapin, E. C., Martin, J. M., Daffer, W., & Hensley, S. (2005). An assessment of the SRTM topographic products (143 p). Pasadena, California: Technical Report JPL D-31639, Jet Propulsion Laboratory.
Bolten, A., & Bubenzer, O. (2006). New elevation data (SRTM/ASTER) for geomorphological and geoarchaeological research in arid regions. Zeitschrift für Geomorphologie Suppl., 142, 265–279.
U.S. Geological Survey (2012b). MODIS overview. Retrieved 19 Mar, 2012, from https://lpdaac.usgs.gov/products/modis_overview.
NASA (2011). Product TRMM_3B43. Retrieved 19 Apr, 2012, from http://mirador.gsfc.nasa.gov/collections/TRMM_3B43__006.shtml.
NASA (2012). Landsat 7. Retrieved 19 Apr, 2012, from http://landsat.gsfc.nasa.gov/about/L7_td.html.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
Copyright information
© 2014 Springer International Publishing Switzerland
About this chapter
Cite this chapter
Fricke, K. (2014). Water Balance Model. In: Analysis and Modelling of Water Supply and Demand Under Climate Change, Land Use Transformation and Socio-Economic Development. Springer Theses. Springer, Cham. https://doi.org/10.1007/978-3-319-01610-8_3
Download citation
DOI: https://doi.org/10.1007/978-3-319-01610-8_3
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-01609-2
Online ISBN: 978-3-319-01610-8
eBook Packages: Earth and Environmental ScienceEarth and Environmental Science (R0)